Written Report

Abtract

This project pulls from a few different files all regarding information about national parks in the United States that I used to create a shiny app with the purpose of providing a very basic education about national parks. To build the map I used a shape file from the national park service to plot all the areas that they manage. This not only includes those with the national park title, but also every designation of a national part site (which is quite an extensive list). To add onto the map, I scraped the National Parks Wikipedia page to get some extra information about the true national parks so users could see some more information when they clicked on a chosen park. In addition to the map, there are data tables that list out relevant information for the national parks and other areas featured on the map. I also used more data provided by the National Parks Service to plot information regarding the amount of visitors to each of the national parks over a range of years. This data was used to create a couple of graphs displaying visitor trends in national parks.

Introduction

This app utilizes data and visualizations to offer an opportunity for expanding knowledge about our national parks and delivering a fundamental education about them.

The map and data tables use the following information:

A shape file provided by the National Park Service. The variables I used from this file are:

• UNIT_NAME, The name of the park, site, or area that will appear on the map. This is what shows when the user hovers over any of the blue areas and is also used as the name for the data table “All_Parks”.
• UNIT_TPE, The classification of each area that the park service manages. This is displayed on the data table “All_Parks” and the user can view areas by type classification.
• STATE, The state each area is in, displayed on the “All_Parks” data table and the user can view areas by state.
• METADATA, The link to the national park service page about each area doesn’t actually provide much information but is displayed on the “All_Parks” data table.

To designate the areas with the “National Park” title and separate them for plotting on the map and the data tables, I used the data that I scraped from Wikipedia and joined them by name. The relevant variables from Wikipedia are:

• Name, The name of the National Park. This is used in the map when the user clicks on green areas and is also displayed in the data table “Just_National_Parks”
• State, The state the park is located in. Appears in “Just_National_Parks” table and the user can view parks by state designation.
• Established, Gives the date the park was established. This appears in the popup window when a park is clicked on and can also be used in the table “Just_National_Parks” to sort by oldest or newest parks.
• Area (in acres), Gives the size of the parks in acres. This can be used to sort the parks in the “Just_National_Parks” by size.
• Visitors in 2022), Shows the amount of visitors to each park in 2022. This appears in the popup window and can also be used to sort “Just_National_Parks” by amount of visitors.
• Description, A brief description of each park. This appears in the popup window and the data table “Just_National_Parks”.

Creating the map boosts user interaction with information about national parks and creates an interesting visualization of these areas. It displays the size and geographic location of each area to help users get a better idea of where they are and how much space is covered by parks and other national sites in the country. The data tables provide a gathered place of information that allows for the posing of questions about the areas shown in the map. This is where the majority of questions and education about national parks takes place. The information from the Wikipedia page allows users to explore details of these areas like the oldest/newest park or the biggest/smallest park, and many more investigative questions.

The visitors plots use the following information:

– An excel file published by the National Parks Service containing the visitor count for 400 national park sites from 1906 to 2016. The variables I used are:

• Unit Name, The name of the park or area
• Unit Type, The classification type of the area
• Visitors, A visitor count for each year along with a collective total amount
• YearRaw, Each year that the data was collected and a total amount for all years (labeled “Total”)

Using this data I created two interactive graphs that allow the user to view the visitors over a range of years, either looking at a collection of parks selected by the user or one park specifically to view more in depth. Adding this information allows the user to learn about visitor trends and how highly trafficked some of these areas are. And while this data set does provide visitation numbers for 400 of the areas the national park service manages, I filtered it down to just keep the areas with the “National Park” classification to simplify the options and visuals. I also changed the year range from 1905 to 2016, to 1995 through 2016 in order to provide more relevant information and reduce the clutter of the visuals. Some of the questions that can be posed using the addition of this data include the most/least popular year for a chosen park, which out of a group of parks was most visited in a chosen year(s), and general trends of visitors.

Visualizations

Map with popup

This is the map that I created using the national parks shape file joined with the information scraped from the Wikipedia page. It is color coded to indicate the difference between the areas labeled as National Park with more information (green) and the other areas managed by the park service (blue). The green areas provide a popup with the additional information, while the blue areas only provide the name of the area when hovered over. However, given the large size of the shape file, I can only publish a visualization with one of the data sets. So the published version can only show the green areas I am using to show those with the title of National Park.

Data table

The map is accompanied by a data table that provides more information on the areas a user is interested in. Here is a small sample, just using Acadia National Park, of the table that appears for those looking for more information about the true national parks. The data tables provide a lot more information about the areas that appear on the map and can be used to answer many of the questions posed in this app.

Visitors Line Plot

This is the more interesting plot regarding the amount of visitors in each park. This version shows the ten parks with the highest total visitor count in the data set. In the shiny app, the graph appears blank and the user must select the parks they want to view before anything appears. As soon as one park is selected it populates on the graph and users can select as many national parks to view as they want. It also sets the year range they are viewing to 2000 through 2016, but the user can alter the range to cover any number of years from 1995 to 2016.

The other visitors graph is built to be more specific and shows a bar graph for a single park, allowing for the selection of any one park but it is set from 1995 to 2016 and doesn’t allow the user to change it. This makes it easier to investigate one park at a time, but it is a more boring visual and requires less user input.

The visualizations are more interactive on the shiny app, linked below https://denali01.shinyapps.io/final_app/

As mentioned earlier, the purpose of this project was to give a basic education about national parks. The visuals and data in the shiny app provide the information to gain that education and to help guide through this process I created a question sheet with some relevant questions to the data. This gives a starting point to the questions that can be answered using the app and the information that can be gained using it. Here’s a brief example of the sheet to give an idea:

Section 1

Use the map and data tables to answer the following:

1. What is the oldest national park and when was it established?

Code

# Yellowstone. It was established on March 1, 1872

2. What is the newest national park and when was it established?

Code

# White Sands. It was established on December 20, 2019

Section 2

Use the collective visitors plot to answer the following:

1. Select 3 of your favorite parks

1. Which one had the most visitors in 2000? How many did it have?
2. How about the most visitors in 2016? Is it the same park as part a?

Section 3

Use the single park visitors plot to answer the following:

1. Select Yellowstone National Park

1. What year did Yellowstone record the most visitors in this time period?

Code

# In 2016, with 4,257,177 visitors 

2. What year did it record the least visitors?

Code

# In 2001, with 2,758,526

Conclusion

After finishing the project and looking back at what I’ve done, I probably would have chosen a similar way to do this project without using such a large shape file and finding a source I could gather all the data I used in a more uniform manner. The large size of the shape file led to a lot of issues with rendering, publishing, and sharing it. This was discouraging because I spent so much time on it but the full version will only run on my computer and can’t be displayed on an app or rendered file. I also would have liked to clean up the app a little more if I had more time to devote to it. I think it could still be cleaner and probably better organized if I dedicated more time towards it. If I continue to work on this app, which I kind of want to just to see how far I can take it, I would do all the cleaning I could manage and I want to add in a tab linking to Google trends to show a real time interest in these areas.